mirror of
https://gitlab.com/libeigen/eigen.git
synced 2024-12-15 07:10:37 +08:00
86 lines
2.8 KiB
C++
86 lines
2.8 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
|
|
// for linear algebra.
|
|
//
|
|
// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
|
|
//
|
|
// Eigen is free software; you can redistribute it and/or
|
|
// modify it under the terms of the GNU Lesser General Public
|
|
// License as published by the Free Software Foundation; either
|
|
// version 3 of the License, or (at your option) any later version.
|
|
//
|
|
// Alternatively, you can redistribute it and/or
|
|
// modify it under the terms of the GNU General Public License as
|
|
// published by the Free Software Foundation; either version 2 of
|
|
// the License, or (at your option) any later version.
|
|
//
|
|
// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
|
|
// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
|
|
// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
|
|
// GNU General Public License for more details.
|
|
//
|
|
// You should have received a copy of the GNU Lesser General Public
|
|
// License and a copy of the GNU General Public License along with
|
|
// Eigen. If not, see <http://www.gnu.org/licenses/>.
|
|
|
|
#include "main.h"
|
|
|
|
template<typename MatrixType> void replicate(const MatrixType& m)
|
|
{
|
|
/* this test covers the following files:
|
|
Replicate.cpp
|
|
*/
|
|
typedef typename MatrixType::Index Index;
|
|
typedef typename MatrixType::Scalar Scalar;
|
|
typedef typename NumTraits<Scalar>::Real RealScalar;
|
|
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
|
|
typedef Matrix<Scalar, Dynamic, Dynamic> MatrixX;
|
|
typedef Matrix<Scalar, Dynamic, 1> VectorX;
|
|
|
|
Index rows = m.rows();
|
|
Index cols = m.cols();
|
|
|
|
MatrixType m1 = MatrixType::Random(rows, cols),
|
|
m2 = MatrixType::Random(rows, cols);
|
|
|
|
VectorType v1 = VectorType::Random(rows);
|
|
|
|
MatrixX x1, x2;
|
|
VectorX vx1;
|
|
|
|
int f1 = internal::random<int>(1,10),
|
|
f2 = internal::random<int>(1,10);
|
|
|
|
x1.resize(rows*f1,cols*f2);
|
|
for(int j=0; j<f2; j++)
|
|
for(int i=0; i<f1; i++)
|
|
x1.block(i*rows,j*cols,rows,cols) = m1;
|
|
VERIFY_IS_APPROX(x1, m1.replicate(f1,f2));
|
|
|
|
x2.resize(2*rows,3*cols);
|
|
x2 << m2, m2, m2,
|
|
m2, m2, m2;
|
|
VERIFY_IS_APPROX(x2, (m2.template replicate<2,3>()));
|
|
|
|
x2.resize(rows,f1);
|
|
for (int j=0; j<f1; ++j)
|
|
x2.col(j) = v1;
|
|
VERIFY_IS_APPROX(x2, v1.rowwise().replicate(f1));
|
|
|
|
vx1.resize(rows*f2);
|
|
for (int j=0; j<f2; ++j)
|
|
vx1.segment(j*rows,rows) = v1;
|
|
VERIFY_IS_APPROX(vx1, v1.colwise().replicate(f2));
|
|
}
|
|
|
|
void test_array_replicate()
|
|
{
|
|
for(int i = 0; i < g_repeat; i++) {
|
|
CALL_SUBTEST_1( replicate(Matrix<float, 1, 1>()) );
|
|
CALL_SUBTEST_2( replicate(Vector2f()) );
|
|
CALL_SUBTEST_3( replicate(Vector3d()) );
|
|
CALL_SUBTEST_4( replicate(Vector4f()) );
|
|
CALL_SUBTEST_5( replicate(VectorXf(16)) );
|
|
CALL_SUBTEST_6( replicate(VectorXcd(10)) );
|
|
}
|
|
}
|